Exposure mapping
Buildings, population, infrastructure and facilities are mapped and overlaid with hazard zones to show what is exposed.
GCRI · Disaster Resilience and Recovery
Geospatial methods for disasters
Geospatial information systems locate hazard, exposure, vulnerability and capacity on the map. In this field they support risk mapping, damage assessment and the coordination of preparedness, response and recovery across agencies.
01Contents
Geospatial methods for disasters in five parts.
02Application
What geospatial information systems does here.
Geospatial information systems capture, store, analyse and present location-referenced data. They provide the common spatial frame for combining hazard, exposure and vulnerability information. In disaster and crisis and climate and hazards, geospatial analysis identifies where hazards overlap critical assets and vulnerable populations. It supports location-based planning across infrastructure, health and finance. The canonical description is on the STEM Commons.
Rapid damage assessment
Satellite and drone imagery is compared before and after events to grade building damage, with field checks to estimate accuracy.
Common operational data
Agencies agree on shared administrative boundaries, place names and baseline layers so that their data can be combined during response.
03Geography
Earth observation in the Philippines.
True-colour imagery, population density and land cover over the Philippines, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
Earth observation, for this page
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
Earth observation, framed on the Philippines.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · U.S. Geological Survey · NASA HLS S30Sources and licences
- We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- NASA Fire Information for Resource Management System (FIRMS), VIIRS 375 m active fire product, NASA LANCE; vector tiles via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
- © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- Live: NASA EONET Events are indicative, not authority warnings.
- Live: U.S. Geological Survey Events are indicative, not authority warnings.
- Observed (EO): NASA HLS S30 (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
- NASA GIBS: We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
- Past year, daily temperature and sunshine (NASA POWER): These data were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program..
- Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
- Optional layers (11 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
Layers and dates
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
- Enhanced vegetation index, rolling 8 days: MODIS Terra EVI, NASA LANCE · 13 Oct 2026
- Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
- Active fires and thermal anomalies: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 2026
04Data
What the method consumes.
Datasets and records used by geospatial information systems on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Data | Role | Label |
|---|---|---|
| OpenStreetMap | Buildings and roads | OBSERVED |
| Global Human Settlement Layer | Built-up area and population | ESTIMATED |
| Common operational datasets on HDX | Shared boundaries and baselines | Published statistics |
| Copernicus EMS mapping | Damage grading | OBSERVED |
05Monitor
Spatial model.
The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.
06Validation
How results are checked.
Positional and attribute accuracy are checked against surveyed control points and reference datasets. Topology rules and metadata standards ensure consistency.
| Check | How it is done |
|---|---|
| Positional accuracy | Layers are checked against reference data |
| Damage grading accuracy | Remote damage grades are compared with field surveys |
| Boundary and code consistency | Datasets use agreed boundaries and place codes |
Errors in projection, scale and data currency propagate through analysis. Aggregation to administrative units can mask local variation.
07Twin and cascade simulator
Model geospatial methods for disasters as a system. Run the cascade.
Assembled from the Nexus Standards area profile Compound and cascading hazard standards: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
Hazards
- Natech event
- Chemical spill or leak (set off downstream)
- Emergency-response overload (set off downstream)
- Toxic gas release (set off downstream)
- Industrial fire (set off downstream)
Systems and couplings
Controls
NS-0Constitution and principlesNS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-9Contextual UNIs (deployments, instances, programme instances)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NRS-H61Hazard family: Cascading failure (NHS-1 sys.cascade)NRS-H62Hazard family: Compound and multi-hazard events (NHS-1 sys.compound)NRS-H60Hazard family: Supply-chain and flow disruption (NHS-1 sys.supply-chain)NRS-H94Hazard family: Systemic cyber events (NHS-1 cyber.systemic-cyber)NRS-H107Hazard family: Digital infrastructure concentration and monoculture (NHS-1 tech.digital-concentration)NRS-H7Hazard family: Large-scale circulation anomalies (NHS-1 atmo.climate-mode)
Observation
- Copernicus EMS rapid mapping activations (listed for reference)
- OpenStreetMap planet and replication (listed for reference)
- ERA5 reanalysis (Copernicus Climate Data Store) (listed for reference)
- Direct economic loss attributed to disasters in relation to global GDP
- Number of disruptions to basic services attributed to disasters
Example geography
- Bangladesh: 134 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Carbon monoxide, smoke transport (AIRS), NASA GIBS
- Vegetation disturbance alerts, 30 m (OPERA DIST-ALERT), NASA GIBS
08Connections
Topics that rely on this method.
09Methods and evidence
How geospatial methods for disasters is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
Uncertainty bands
How far the outlook for geospatial methods for disasters could spread, shown as ranges rather than a single line.
- Central estimate
- median of the ensemble
- Ranges
- likely and very likely, in IPCC calibrated language
- Ensemble
- members, scenarios and initial conditions stated
- Read with
- the sensitivity of the result to each input
FAIR guiding principles · GO FAIR and FORCE11W3C PROV · World Wide Web ConsortiumGuidance on consistent treatment of uncertainties · IPCCCEOS Analysis Ready Data · Committee on Earth Observation Satellites
10Stewardship
Who maintains the method.
Space and Earth Observation stewards geospatial information systems for the Consortium and reviews how it is applied across platforms.
11Process
How the process runs.
Process explorer · Process
Geospatial methods for disasters: Layers to published map
7 steps·4 stages·1 gate
Process
Geospatial methods for disasters: Layers to published map
Layers enter with their rights, are aligned, analysed and checked for uncertainty, then released after public-safe review; a map is a governed spatial claim.
01 Data
- 01Source layers with their rightsDataset · NXS-GRX (canonical data, provenance and risk)Spatial views of The Global Risks Index (NXS-GRX) products sit under the boundary licence gate. Rights classification sets how a layer may be used.
02 Harmonise
- 02Coordinate reference and boundary versionRecord · NXS-EOP (earth observation and digital twins)The area of interest preserves its coordinate reference system, polygon validity and observation support. Boundary versions are kept.
- 03Harmonise units, variables and timeStepUnit metadata, conversion records and transformation logs are required. Alignment is an evidence event, not hidden preprocessing.
03 Analyse and check
- 04Analyse with a recorded processing recipeModel · GIS teamA processing recipe records parameters, calibration, inputs and output lineage. The analysis methods are named in each product's own record.
- 05Spatial uncertainty checkGateSpatial uncertainty is recorded and affects downstream use. A high-uncertainty polygon may suit internal review, not public-safe release.
04 Publish
- 06Spatial metadata bundleRecordThe bundle records boundary type, jurisdiction, geometry version, projection, resolution, source, time window, uncertainty and access class.
- 07Public-safe release of the mapDecisionThe output record names the redactions, uncertainty and public-safe reviewer. A map is a governed spatial claim, never merely a picture.
Spatio-temporal intelligence · Data protocols: semantic, jurisdictional and temporal intelligence · NXS-EOPDesigned programme process, not a record of operation. No cycle has run and every programme is at service level R0. A gate is a programme decision, never a public-authority approval, certification or deployment authorisation. The pages cited are design doctrine.
12Connected
Where this page leads across the Consortium.
13Questions
Questions and answers.
What are the limits of geospatial information systems in this field?
Errors in projection, scale and data currency propagate through analysis. Aggregation to administrative units can mask local variation.
How are results checked?
Positional and attribute accuracy are checked against surveyed control points and reference datasets. Topology rules and metadata standards ensure consistency.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method's use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
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GCRIDisaster Resilience and RecoveryCountry Systems Risk and ResilienceEvidence Brief
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